st: Overidentification test in clogit

I am trying to estimate a model that explains the choice
of selling on a specific market (in my case on the farm, in the local market,
on a distant wholesale market) on a number of (a) farmer, (b) market, and (c) transaction
characteristics.

Data are by transaction, some households sell their
harvest in more that one transactions so I have 120 households and 280 transactions
approximately.

One of my explanatory variable in the conditional logit
is quantities sold which is endogenous to the market choice (I decide where and
how much to sell simultaneously). I therefore want to instrument the quantity
and have estimated a predicted value with a first stage OLS regression. My
questions:

1) How can I test that the instruments are valid, that is
that the exogenous variables included in the OLS are indeed exogenous? In a
normal 2sls this is trivial, but in this type of mixed ‘clogit’
(see Long & Freese, p. 243) data are transformed so that the number of
observations is now different from the first stage OLS model (observations are
multiplied by the number of alternatives).

2) Is the fact that both my regressions are clustered (to
control for household fixed effects) a problem?

3) Commands like overid use a Sargan test that is based on
R2. How does the fact that clogit yields a (variety of) pseudo-R2 (with all their
problems) affect the possibility of meaningfully performing a test along those
lines?